Chapter 6 Elements

6.1 Element level

GIFTs_elements_community_merged<-GIFTs_elements_community %>%
    as.data.frame() %>%
    rownames_to_column(var="sample") %>%
    pivot_longer(!sample,names_to="trait",values_to="gift") %>%
    left_join(sample_metadata, by = join_by(sample == Tube_code))%>%
    mutate(functionid = substr(trait, 1, 3)) %>%
    mutate(trait = case_when(
      trait %in% GIFT_db$Code_element ~ GIFT_db$Element[match(trait, GIFT_db$Code_element)],
      TRUE ~ trait
    )) %>%
    mutate(functionid = case_when(
      functionid %in% GIFT_db$Code_function ~ GIFT_db$Function[match(functionid, GIFT_db$Code_function)],
      TRUE ~ functionid
    )) %>%
    mutate(trait=factor(trait,levels=unique(GIFT_db$Element))) %>%
    mutate(functionid=factor(functionid,levels=unique(GIFT_db$Function)))

# Create an interaction variable for time_point and sample
GIFTs_elements_community_merged$interaction_var <- interaction(GIFTs_elements_community_merged$sample, GIFTs_elements_community_merged$time_point)
  
ggplot(GIFTs_elements_community_merged,aes(x=interaction_var,y=trait,fill=gift)) +
        geom_tile(colour="white", linewidth=0.2)+
        scale_fill_gradientn(colours=rev(c("#d53e4f", "#f46d43", "#fdae61", "#fee08b", "#e6f598", "#abdda4", "#ddf1da")))+
        facet_grid(functionid ~ type, scales="free",space="free") +
        theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1),
              strip.text.y = element_text(angle = 0)) + 
        labs(y="Traits",x="Time_point",fill="GIFT")+
  scale_x_discrete(labels = function(x) gsub(".*\\.", "", x))

6.2 Comparison of samples from the 0 Time_point (0_Wild)

sample_metadata_wild <- sample_metadata%>% 
  filter(time_point == "0_Wild")

element_gift_wild <- GIFTs_elements_community %>% 
  as.data.frame() %>% 
  rownames_to_column(., "Tube_code") %>% 
  inner_join(., sample_metadata_wild[c(1,3)], by="Tube_code")
# Find numeric columns
numeric_cols <- sapply(element_gift_wild, is.numeric)

# Calculate column sums for numeric columns only
col_sums_numeric <- colSums(element_gift_wild[, numeric_cols])

# Identify numeric columns with sums not equal to zero
nonzero_numeric_cols <- names(col_sums_numeric)[col_sums_numeric != 0]

# Remove numeric columns with sums not equal to zero
filtered_data <- element_gift_wild[, !numeric_cols | colnames(element_gift_wild) %in% nonzero_numeric_cols]
significant_elements_wild <- filtered_data %>%
  pivot_longer(-c(Tube_code,species), names_to = "trait", values_to = "value") %>%
  group_by(trait) %>%
  summarise(p_value = wilcox.test(value ~ species, exact=FALSE)$p.value) %>%
  mutate(p_adjust=p.adjust(p_value, method="BH")) %>%
  filter(p_adjust < 0.05)  %>%
  left_join(.,uniqueGIFT_db[c(1,3)],by = join_by(trait == Code_element))

element_gift_t <- element_gift_wild  %>% 
  dplyr::select(-c(species))  %>% 
  t() %>%
  row_to_names(row_number = 1) %>%
  as.data.frame() %>%
  mutate_if(is.character, as.numeric)  %>%
  rownames_to_column(., "trait")

element_gift_filt <- subset(element_gift_t, trait %in% significant_elements_wild$trait) %>% 
  t() %>%
  row_to_names(row_number = 1) %>%
  as.data.frame() %>%
  mutate_if(is.character, as.numeric)  %>%
  rownames_to_column(., "Tube_code")%>% 
  left_join(., sample_metadata_wild[c(1,3)], by = join_by(Tube_code == Tube_code))

element_gift_filt %>%
  dplyr::select(-Tube_code)%>%
  group_by(species)  %>%
  summarise(across(everything(), mean))%>%
  t() %>%
  row_to_names(row_number = 1) %>%
  as.data.frame() %>%
  mutate_if(is.character, as.numeric)  %>%
  rownames_to_column(., "Elements")  %>%
  left_join(.,uniqueGIFT_db[c(1,3)],by = join_by(Elements == Code_element))

element_gift_names <- element_gift_filt%>%
  dplyr::select(-species)%>%
  t() %>%
  row_to_names(row_number = 1) %>%
  as.data.frame() %>%
  mutate_if(is.character, as.numeric)  %>%
  rownames_to_column(., "Elements")  %>%
  left_join(.,uniqueGIFT_db[c(1,3)],by = join_by(Elements == Code_element))%>%
  dplyr::select(-Elements)%>%
  dplyr::select(Function, everything())%>%
  t()%>%
  row_to_names(row_number = 1) %>%
  as.data.frame() %>%
  mutate_if(is.character, as.numeric)  %>%
  rownames_to_column(., "Tube_code")%>% 
  left_join(., sample_metadata_wild[c(1,3)], by = join_by(Tube_code == Tube_code))

6.2.1 Plot

colNames <- names(element_gift_names)[2:34] #always check names(element_gift_names) first to know were your traits finish
for(i in colNames){
  plt <- ggplot(element_gift_names, aes(x=species, y=.data[[i]], color = species)) +
    geom_boxplot(alpha = 0.2, outlier.shape = NA, width = 0.3, show.legend = FALSE) +
    geom_jitter(width = 0.1, show.legend = TRUE) +
    theme_minimal() +
    theme(
      axis.line = element_line(size = 0.5, linetype = "solid", colour = "black"),
      panel.grid.major = element_blank(),
      panel.grid.minor = element_blank(),
      panel.border = element_blank())
  print(plt)
}

6.3 Comparison of samples from the 6th Time_point (6_Post-FMT2)

sample_metadata_TM6 <- sample_metadata%>% 
  filter(time_point == "6_Post-FMT2")%>% 
  filter(type != "Hot_control")

element_gift_TM6 <- GIFTs_elements_community %>% 
  as.data.frame() %>% 
  rownames_to_column(., "Tube_code") %>% 
  inner_join(sample_metadata_TM6 %>% select(1, 7), by = "Tube_code")
# Find numeric columns
numeric_cols <- sapply(element_gift_TM6, is.numeric)

# Calculate column sums for numeric columns only
col_sums_numeric <- colSums(element_gift_TM6[, numeric_cols])

# Identify numeric columns with sums not equal to zero
nonzero_numeric_cols <- names(col_sums_numeric)[col_sums_numeric != 0]

# Remove numeric columns with sums not equal to zero
filtered_data <- element_gift_TM6[, !numeric_cols | colnames(element_gift_TM6) %in% nonzero_numeric_cols]
significant_elements_TM6 <- filtered_data %>%
  pivot_longer(-c(Tube_code,type), names_to = "trait", values_to = "value") %>%
  group_by(trait) %>%
  summarise(p_value = wilcox.test(value ~ type, exact=FALSE)$p.value) %>%
  mutate(p_adjust=p.adjust(p_value, method="BH")) %>%
  filter(p_value < 0.05)  %>% #take into account that p_value is used and not p_adjust
  left_join(.,uniqueGIFT_db[c(1,3)],by = join_by(trait == Code_element))

element_gift_t <- element_gift_TM6  %>% 
  dplyr::select(-c(type))  %>% 
  t() %>%
  row_to_names(row_number = 1) %>%
  as.data.frame() %>%
  mutate_if(is.character, as.numeric)  %>%
  rownames_to_column(., "trait")

element_gift_filt <- subset(element_gift_t, trait %in% significant_elements_TM6$trait) %>% 
  t() %>%
  row_to_names(row_number = 1) %>%
  as.data.frame() %>%
  mutate_if(is.character, as.numeric)  %>%
  rownames_to_column(., "Tube_code")%>% 
  left_join(., sample_metadata_TM6[c(1,7)], by = join_by(Tube_code == Tube_code))

element_gift_filt %>%
  dplyr::select(-Tube_code)%>%
  group_by(type)  %>%
  summarise(across(everything(), mean))%>%
  t() %>%
  row_to_names(row_number = 1) %>%
  as.data.frame() %>%
  mutate_if(is.character, as.numeric)  %>%
  rownames_to_column(., "Elements")  %>%
  left_join(.,uniqueGIFT_db[c(1,3)],by = join_by(Elements == Code_element))

element_gift_names <- element_gift_filt%>%
  dplyr::select(-type)%>%
  t() %>%
  row_to_names(row_number = 1) %>%
  as.data.frame() %>%
  mutate_if(is.character, as.numeric)  %>%
  rownames_to_column(., "Elements")  %>%
  left_join(.,uniqueGIFT_db[c(1,3)],by = join_by(Elements == Code_element))%>%
  dplyr::select(-Elements)%>%
  dplyr::select(Function, everything())%>%
  t()%>%
  row_to_names(row_number = 1) %>%
  as.data.frame() %>%
  mutate_if(is.character, as.numeric)  %>%
  rownames_to_column(., "Tube_code")%>% 
  left_join(., sample_metadata_TM6[c(1,7)], by = join_by(Tube_code == Tube_code))

6.3.1 Plot

colNames <- names(element_gift_names)[2:20] #always check names(element_gift_names) first to now were your traits finish
for(i in colNames){
  plt <- ggplot(element_gift_names, aes(x=type, y=.data[[i]], color = type)) +
    geom_boxplot(alpha = 0.2, outlier.shape = NA, width = 0.3, show.legend = FALSE) +
    geom_jitter(width = 0.1, show.legend = TRUE) +
    theme_minimal() +
    theme(
      axis.line = element_line(size = 0.5, linetype = "solid", colour = "black"),
      panel.grid.major = element_blank(),
      panel.grid.minor = element_blank(),
      panel.border = element_blank())
  print(plt)
}